File size: 15,658 Bytes
869ae69
1
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    MultiInputActorClass policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space (Tuple)\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Uses the CombinedExtractor\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f18d93adab0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f18d93b23c0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1683826584393204779, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[0.3222821  0.00526062 0.5322651 ]\n [0.3222821  0.00526062 0.5322651 ]\n [0.3222821  0.00526062 0.5322651 ]\n [0.3222821  0.00526062 0.5322651 ]]", "desired_goal": "[[ 0.8694546   0.93847024  0.211516  ]\n [-0.20937268 -0.9777553   0.03549874]\n [-0.60335296 -0.09872239 -1.2384014 ]\n [ 1.283504    1.6539532   0.27346358]]", "observation": "[[ 0.3222821   0.00526062  0.5322651   0.06744412 -0.00347482  0.06005844]\n [ 0.3222821   0.00526062  0.5322651   0.06744412 -0.00347482  0.06005844]\n [ 0.3222821   0.00526062  0.5322651   0.06744412 -0.00347482  0.06005844]\n [ 0.3222821   0.00526062  0.5322651   0.06744412 -0.00347482  0.06005844]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]]", "desired_goal": "[[-0.11511245 -0.03910835  0.10540683]\n [ 0.10547453 -0.04911312  0.2874218 ]\n [ 0.14112525 -0.1231889   0.26603928]\n [-0.05539724 -0.12162333  0.11654403]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 31250, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}